Improved speech recognition using a reduced auditory representation

The information produced by a straightforward auditory model, like the original speech signal, is subject to extreme local variability and is not suitable for direct presentation to speech recognition algorithms. Therefore, an analysis is required which will make the important features of the neural firing patterns explicit, but which will describe them concisely and without disruption by known characteristics of speech. Several attempts have been made to develop such an analysis, however, such analyses ignore significant aspects of neural firing patterns, and consequently information is lost (usually that associated with fine temporal structure). The authors describe a `reduced auditory representation´, which retains more information, and presents the results of preliminary recognition experiments using this data